Wafer inspection system

ABSTRACT

A method and system for identifying a defect or contamination on a surface of a material. The method and system involves providing a material, such as a semiconductor wafer, using a non-vibrating contact potential difference sensor to scan the wafer, generate contact potential difference data and processing that data to identify a pattern characteristic of the defect or contamination.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application is related to as a continuation-in-part and claimspriority from copending U.S. patent application Ser. No. 10/631,469 fileJul. 29, 2003 which claims priority from U.S. Prov. Pat. App. Ser. No.60/444,504 filed Feb. 3, 2003.

FIELD OF THE INVENTION

The present invention is directed to methods and systems for theinspection of semiconductor wafers and other materials such asintegrated circuits (IC) and any surface benefiting from inspection.Hereinafter, any material susceptible of surface inspection by thesystem herein described contact potential difference imaging device willbe denoted a “wafer”. More particularly, the present invention isdirected to a method and system for the characterization of microscopicand macroscopic defects through imaging and visualization of the contactpotential difference topology on the wafer surface through the use of anon-vibrating contact potential difference sensor.

BACKGROUND OF THE INVENTION

The multi-billion dollar global market for semiconductor defectmanagement is growing both in absolute terms and as a percentage ofsemiconductor capital equipment investment. In general, there are twofactors that determine the economics of a semiconductor fabricationfacility at a given utilization level, namely throughput and yield. Ascomplex new technologies such as 300 mm wafers, copper interconnects,and reduced feature (circuit) sizes drive the margin of error infabrication ever lower, new inspection technologies are critical to keepyields high and bottom-line economics attractive. Detection andelimination of chemical contamination and other types of defects is aconstant concern for semiconductor manufacturers and equipmentsuppliers. Contamination can arise from use of processing chemicals,processing equipment, and poor handling techniques. Contaminants caninclude, for example, metals, carbon, and organic compounds. Other typesof defects can result from a wide range of causes, including flaws inthe semiconductor crystal, improper processing, improper handling, anddefective materials. In addition, many cleaning steps are required inwafer fabrication, such as but not limited to the semiconductorindustry. Each step is time consuming and requires expensive chemicalsthat may require special disposal procedures. Existing methods formonitoring or controlling these processes are expensive and timeconsuming. As a result, wafers are often cleaned for a longer period oftime and using more chemicals than are required.

Defect detection and characterization systems can be divided intoin-line and off-line systems. “In-line” refers to inspection andmeasurement that takes place inside the clean room where wafers areprocessed. “Off-line” refers to analysis that takes place outside of thewafer processing clean room, often in a laboratory or separate cleanroom that is located some distance from the manufacturing area. Inaddition, many of these analytical techniques are destructive, whichrequires either the sacrifice of a production wafer or the use ofexpensive “monitor” wafers for analysis. In-line inspection andmeasurement is crucial for rapidly identifying and correcting problemsthat may occur periodically in the manufacturing process. A typicalsemiconductor wafer can undergo over 500 individual process steps andrequire weeks to complete. Each semiconductor wafer can have a finishedproduct value of up to $100,000. Because the number of steps and periodof time, involved in wafer fabrication are so large, a lot of work inprocess can exist at any point in time. It is critical thatprocess-related defects be found and corrected immediately before alarge number (and dollar value) of wafers are affected. Such defects,regardless of the nature of the wafer, semiconductor, IC, or otherdevice, are detrimental to performance and diminish productivity andprofitability.

Many types of defects and contamination are not detectable usingexisting in-line tools, and these are typically detected and analyzedusing expensive and time-consuming “off line” techniques (describedbelow) such as Total Reflectance X-ray Fluorescence (TXRF), Vapor PhaseDecomposition Inductively Coupled Plasma-Mass Spectrometry (VPD ICP-MS)or Secondary Ion Mass Spectrometry (SIMS). Since these techniques areused off-line (outside of the clean room used to process wafers) andusually occur hours, or even days, after the process step that hascaused the contamination, their value is significantly limited.

A brief description of some well known techniques for wafer inspectionand chemical contamination detection are presented in Table 1. This listis not in any sense exhaustive as there are a very large number oftechniques that are used for some type of semiconductor analysis orcharacterization or for other surface inspection of other types ofmaterials.

TABLE 1 In-line/ Analytical Technique Description Off-line Total X-raysirradiate the wafer within the Off-line Reflection critical angle fortotal external X-Ray reflectance, causing surface atoms to Fluorescencefluoresce. (TXRF) Automated Optical images are acquired and In-lineOptical automatically analyzed for detection Microscopy of largedefects. Laser Wafer surface is illuminated with In-line Backscatteringlaser spots and the angle and/or polarization of reflected light isanalyzed to detect and classify particles. Vapor Phase Wafers “scanned”with a drop of HF Off-line Decomposition that is analyzed using massInductively Coupled- spectrometry. Mass Spectrometry (VPD ICP-MS)Secondary Ion beam sputters the wafer surface Off-line Ion Mass creatingsecondary ions that are Spectroscopy analyzed in a mass spectrometer.(SIMS)

Table 2 summarizes some major advantages and disadvantages of eachexample technique. In general, off-line detection techniques areextremely sensitive to tiny amounts of contamination; but are slow,expensive, and complex to operate. Some have limited, or no, imaging orsurface mapping capability, or are destructive in nature. In-linetechniques are much faster, non-destructive, and provide defect mapping,but have limited chemical contamination detection or analysiscapability.

TABLE 2 Analytical Technique Advantages Disadvantages Total ReflectionX- Very sensitive Limited coverage Ray Fluorescence Some mappingcapability Unpatterned wafers (TXRF) Nondestructive only AutomatedOptical Fast Very limited chemical Microscopy Relatively low cost andparticle detection Detects a wide range of macro defects (>50 microns)Imaging of wafer surface Non-contact/non- destructive LaserBackscattering Fast Only detects Relatively low cost particles - noDetects very small chemistry particles Imaging of water surfaceNon-contact/non- destructive Vapor Phase Very sensitive DestructiveDecomposition Able to identify wide Slow Inductively Coupled- range ofcontaminants Expensive Mass Spectrometry Complex (VPD ICP-MS) Cannotimage Only works on bare silicon Secondary Ion Mass Very sensitiveExpensive Spectroscopy (SIMS) Detects a wide range of Slow contaminantsDestructive Sub-surface detection

In general, existing in-line wafer inspection tools operate atproduction speeds and generate images of the wafer surface that areprocessed to identify and locate defects. However, these techniques are,as mentioned above, very limited in their ability to detect chemicalcontamination. Laser backscattering systems are limited to detectingparticles down to sub-micron sizes, and optical microscopy systems canonly detect chemical contamination that results in a visible stain orresidue. Both techniques lack the ability to identify or classify thechemical composition of the particle or contamination. Off-linelaboratory techniques are used to qualify the cleanliness of newprocesses and equipment, or to analyze defects detected by in-lineequipment or as part of failure analysis.

Another system that has been investigated is the use of ContactPotential Difference imaging (CPD). CPD refers to the electrical contactbetween two different metals and the electrical field that develops as aresult of the differences in their respective maximum electronic energylevel, i.e. their respective Fermi energies. When two metals are placedin contact, the Fermi energies of each will equilibrate by the flow ofelectrons from the metal with the lower Fermi energy to that of thehigher. “Vibrating CPD sensor” refers to the vibration of one metalrelative to the other in a parallel plate capacitor system. Thevibration induces changes in the capacitance with time, and therefore asignal related with the surface profile. A CPD signal can also begenerated by the translation of one surface past a reference samplethrough the use of a non-vibrating contact potential difference (nvCPD)sensor(s). This translation makes high speed scanning possible.

However, even these nvCPD sensors can themselves present certaindifficulties. At a microscopic level, the surfaces of wafers are notflat due to wafer thickness variation, materials on the surface,“bowing”, and other factors. In order to scan the wafer at a close butsafe (i.e., close to the surface to promote good signal strength but farenough away to minimize any possibility of impacting the wafer surface)distance, an appropriate sensor height must be calculated and set. Thus,the height of the sensor above the wafer surface must be measured andcontrolled to produce repeatable results. Furthermore, height control isalso necessary to minimize the sensor height to improve resolution andsignal strength. However, height is difficult to control and measure, asis the appropriate height for each specific wafer.

It is possible to use one of many commercially available height sensorsto control the height of the nvCPD sensor above the wafer surface. Thisrequires the expense of an additional sensor, and the added complexityof a calibration routine to determine the position of the nvCPD sensortip relative to measurements made by the separate height sensor.

A related problem is the difficulty in establishing a point of referencefor all distance measurements, including height, related to an nvCPDscan. A reference point is needed to produce useful measurement data forimage production.

In some sensor systems, such as nvCPD sensors, it is necessary toseparate the sharp peak signal from the other two components of thesignal (low frequency signal and induced noise signals) to locate andmeasure the contaminated areas of a wafer. This is challenging becausethe sharp peak signal behaves like noise, i.e., it consists of sharppeaks that alternate their polarity in high frequency mode. Because ofthis, conventional high frequency filters based on the frequency domainonly do not work, as they would degrade the sharp peak signalsignificantly along with the noise.

In addition, an nvCPD signal is generally delayed in time, which impactson the quality of the nvCPD signal/image. As the sampling timeincreases, the time delay becomes larger. The time delay may beexplained by the equivalent RC circuit modeling the electrical signalpath from the probe tip to the output of the A/D converter through theamplifier, the data acquisition board and the connecting lines betweenthem. The equivalent capacitance is mixed with the capacitance betweenthe probe and the wafer surface, the parasitic capacitance of theconnecting lines, the internal capacitance of the amplifier, and otherknown conventional effects. The result is that minute feature signalsare less detectable, and the signal magnitude and thus thesignal-to-noise ratio are smaller.

A critical need therefore exists for a fast, inexpensive, and effectivemeans of detecting, locating, and classifying relatively smallquantities of chemical content and physical features on wafers. Inaddition, there is a need for a system which minimizes cost andcomplexity of the sensor control mechanisms, such as height control.Furthermore, there is a need for methods and systems that have improvedsignal processing.

It is therefore an object of the invention to provide an improved methodand system for inspection of surfaces of any materials, such assemiconductor wafers and other electronic devices.

It is an additional object of the invention to provide an improvedmethod and system for providing images of surface defects on asemiconductor wafer or an integrated circuit device.

It is yet another object of the invention to provide an improved methodand system for identifying different classes of wafer surface defects bypattern recognition.

It is still a further object of the invention to provide an improvedmethod and system for classifying categories of surface defects onsemiconductor wafers, including without limitation surface defectstates, electrostatic field variations, oxide states and chemicalcontamination.

It is also an additional object of the invention to provide an improvedmethod and system for sensing electrostatic fields arising fromsemiconductor wafer surface defects.

It is yet another object of the invention to provide an improved methodand system for detecting the presence of thin dielectric films onsurfaces of semiconductor wafers and to detect film defects such aspinholes, bubbles, delaminations, or contamination under the film.

It is a further object of the invention to provide an improved methodand system to sense variations in oxide states on semiconductor wafersurfaces.

It is also a further object of the invention to provide an improvedmethod and system to classify particulate contaminants on semiconductorwafers identified initially by optical inspection systems.

It is yet a further object of the invention to provide an improvedmethod and system for detecting variations in dopant concentration ofsemiconductor wafers.

It is another object of the invention to provide an improved method andsystem for use of an nvCPD sensor to inspect the surface quality ofsemiconductor wafers.

It is still another object of the invention to provide an improvedmethod and system of nvCPD sensors in combination with other inspectionsystems for evaluating semiconductor wafer surface properties.

It is a further object of the invention to provide an improved methodand system for producing topological images of differing contactpotential characteristic of defects on a semiconductor wafer.

It is also an object of the invention to provide an improved method andsystem for rapidly scanning the surface of a semiconductor wafer toidentify sub-microscopic, microscopic and macroscopic surface defectscharacterized by potential field disturbances on the wafer surface.

It is also an object of the invention to provide an improved method andsystem for detecting the cleanliness of a semiconductor wafer todetermine if a cleaning process has eliminated all contaminants and toavoid the time and expense of cleaning wafers for longer than isnecessary to remove contaminants or to perform unnecessary processingsteps.

In each case described above, wafer surface can refer to the front-side(patterned side) of the wafer, back-side (unpatterned side) of thewafer, or the edge of the wafer or any surface undergoing inspectionregardless of the type of material.

Other objects, features and advantages of the present invention will bereadily apparent from the following description of the preferredembodiment thereof, taken in conjunction with the accompanying drawingsdescribed below.

SUMMARY OF THE INVENTION

The present invention provides a wafer inspection system that is a fast,inexpensive, and effective means of detecting, locating, and classifyingrelatively small quantities of chemical content, and physical featureson wafers, such as but not limited to semiconductor production,integrated circuit devices, or any material which may benefit from suchinspections, while allowing for a minimization of the complexity of thesensor control mechanisms and an improvement in signal processing. Inone preferred example embodiment, a wafer inspection system of thepresent invention includes steps for identifying a defect on a surfaceof a semiconductor wafer. In a preferred embodiment, the steps compriseproviding a semiconductor wafer; providing a non-vibrating contactpotential difference sensor; scanning the semiconductor wafer relativeto the non-vibrating contact potential difference sensor; generatingcontact potential difference data from the non-vibrating sensor; andprocessing the non-vibrating contact potential difference sensor data toautomatically detect a pattern that is characteristic of a particulartype of defect.

In addition, the system of the present invention provides, in apreferred embodiment, a method for determining a reference point for thesensor. In addition, in some embodiments of the present invention thesystem includes a method for determining the height of the sensor. Inaddition, the present invention may preferably include a method forcalculating the scan height to allow for wafer height variation.Furthermore, a system in accordance with the principles of the presentinvention preferably includes signal processing methods and devices forimproving the native signal output of the sensor, such as by reducingnoise or reducing signal time delay.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates one embodiment of the nvCPD scanning method andsystem;

FIG. 2 illustrates the concept of the contact potential differencemethodology;

FIG. 3 illustrates an nvCPD scanning method;

FIG. 4 illustrates the current output of an nvCPD probe as it passesover a positive and negative work function transition;

FIG. 5 illustrates axial orientation of the nvCPD system;

FIG. 6 illustrates standard deviation of signals within a scan area;

FIG. 7 illustrates steps for creating test wafers which are partiallycoated with known concentrations of contaminants;

FIG. 8A illustrates one form of scanning nvCPD system with a three axislinear positioning system with the nvCPD sensor and a wafer mounted on ahigh speed spindle; and FIG. 8B illustrates another form of scanningnvCPD system;

FIG. 9 illustrates a flow diagram for the image acquisition process of aradially scanned nvCPD imaging system;

FIG. 10A illustrates an optical image of a 100 mm diameter silicon waferafter application of a vacuum pick-up device and FIG. 10B illustrates annvCPD image of the wafer of FIG. 10A;

FIG. 11A illustrates an optical image of a second silicon wafer afterapplying alcohol while spinning the wafer and allowing the alcohol todry and FIG. 11B is an nvCPD image of the same wafer of FIG. 11A;

FIG. 12A illustrates an optical image of a silicon wafer afterapplication of a latex glove mark and FIG. 12B is an nvCPD image of thesame wafer of FIG. 12A;

FIG. 13A illustrates an optical image of a silicon wafer having humanfingerprints on the wafer and FIG. 13B illustrates an nvCPD image of thewafer of FIG. 13A;

FIG. 14 illustrates an nvCPD image of a silicon wafer after brushing thewafer surface with a stainless steel tool;

FIG. 15 illustrates an nvCPD image of a silicon wafer after pressing analuminum fixture onto the wafer surface;

FIG. 16 illustrates a chart depicting a typical nvCPD signal where thereis a set of peaks comprising a positive peak and a negative peak havingnon-equivalent heights;

FIG. 17 illustrates a chart depicting a signal output of one embodimentof the present invention where the positive peak height is substantiallyequivalent to the negative peak height;

FIG. 18 is a detailed view of the Adjust Starting Position and Height ofProbe Above Surface step of FIG. 9;

FIG. 19 illustrates NCVPD processed wafer images before deconvolution;

FIG. 20 illustrates NCVPD processed wafer images after deconvolution;

FIG. 21A illustrates a wafer map produced in accordance with theprinciples of the present invention, wherein the wafer pattern is oneatomic layer thick over native silicon oxide;

FIG. 21B is a graph showing signal strength along a single probe track;

FIG. 21C is a graph of the signal strength versus the density of goldfor the wafer map depicted in FIG. 21A;

FIG. 22A is a 2D Edge Detection optical view using Canny Algorithm atMultiple Resolutions (#7 Wafer dipped into a CMP Slurry);

FIG. 22B is a 2D Edge Detection image produced in accordance with theprinciples of the present invention using Canny Algorithm at MultipleResolutions (#7 Wafer dipped into a CMP Slurry, threshold=0.00001,Contamination Level=24.5);

FIG. 22C is a 2D Edge Detection image produced in accordance with theprinciples of the present invention using Canny Algorithm at MultipleResolutions (#7 Wafer dipped into a CMP Slurry, threshold=0.008,Contamination Level=4.5);

FIG. 22D is a 2D Edge Detection image produced in accordance with theprinciples of the present invention using Canny Algorithm at MultipleResolutions (#7 Wafer dipped into a CMP Slurry, threshold=0.01,Contamination Level=1.9);

FIG. 22E is a 2D Edge Detection image produced in accordance with theprinciples of the present invention using Canny Algorithm at MultipleResolutions (#7 Wafer dipped into a CMP Slurry, threshold=0.012,Contamination Level=1.1);

FIG. 22F is a 2D Edge Detection image produced in accordance with theprinciples of the present invention using Canny Algorithm at MultipleResolutions (#7 Wafer dipped into a CMP Slurry, threshold=0.014,Contamination Level=0.8);

FIG. 23A an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry);

FIG. 23B an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry,threshold=0.00001, Contamination Level=24.3);

FIG. 23C an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry,threshold=0.005, Contamination Level=9.6);

FIG. 23D an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry,threshold=0.006, Contamination Level=8.2);

FIG. 23E an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry,threshold=0.008, Contamination Level=6.9); and

FIG. 23F an optical image of 2D Edge Detection produced in accordancewith the principles of the present invention using Canny Algorithm atDifferent Scales (Qcept #6 Wafer dipped into a CMP Slurry,threshold=0.009, Contamination Level=6.4).

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A preferred embodiment of the invention is directed to an improved useof an nvCPD sensor. In particular, FIG. 1 illustrates a functional blockflow diagram of components and operation of one preferred form of annvCPD scanning system 10. A nvCPD sensor 12 (see FIG. 2) is based on thephenomena of contact potential difference which is a voltage generatedbetween two dissimilar materials brought in close proximity to eachother. An illustration of this concept can be seen in FIG. 2. In thecase of the wafer scanning system 10, the sensor tip 13 forms a firstplate 14 and a wafer 15 having a wafer surface 16 forms a second plate18 (see FIG. 2.) Probe tip surface 20 of the first plate 14 is made of aconducting material with a fixed work function—generally, the differencein energy between the Fermi level of the solid and the free energy ofthe space outside the solid, including, in metals, the image potentialof electrons just outside the surface. The wafer surface 16 of thesecond plate 18 has a work function which can vary due to irregularitiesin the semiconductor wafer surface 16 or contaminants or other materialsdeposited on the wafer surface 16. When the first plate 14 and thesecond plate 18 are electrically connected, the Fermi levels of therespective surface equilibrate and form an electric field between them.If the work function of the sensor tip 13 is fixed, the magnitude of theelectric field is then related to the distance between the first plate14 and the second plate 18, the relative dielectric between the firstplate 14 and the second plate 18 and the work function of the wafersurface 16. In practice the first plate 14 and the second plate 18equilibrate rapidly providing little to measure. To provide a currentflow that can be measured, some motion of the sensor tip 12 relative tothe wafer surface 16 must be realized. In one embodiment, the nvCPDsensor 12 is moved over the surface at a substantially fixed distanceand variations in the wafer surface 16 cause a current to flow.

An illustration of this concept can be seen in FIG. 3. The current flowfrom this nvCPD sensor 12 can be modeled by the following equation:

$i = {{C\frac{\partial V}{\partial t}} + {V\frac{\partial C}{\partial t}}}$wherein C and V are defined as

$\begin{matrix}{C = \frac{ɛ_{o}ɛ_{r}A}{d}} & {and} & {V = \frac{\Phi_{probe} - \Phi_{wafer}}{e}}\end{matrix}$and further wherein ε_(o) is the permittivity of free space, ε_(r) isthe relative dielectric constant, A is the area of the probe tip, d isthe distance between the sensor tip 13 and the wafer 15, Φ is the workfunction of the respective surface, and e is the charge on an electron.The V term can also be described as a difference in surface potentialsbetween the nvCPD sensor 12 and the wafer 15. In addition the surfacepotentials on the wafer surface 16 can vary due to defects. The overallsurface potential is related to the underlying materials work functionbut it can also be affected by adsorbed layers of material on the wafersurface 16. Even sub mono-layers of materials are known to significantlyaffect the surface potential.

The

${C\frac{\partial V}{\partial t}} \approx {C\frac{{\Phi\;{probe}} - {\Phi\;{wafer}}}{\Delta\; t}}$term is related to changes in work function on the wafer surface 16. Itcan be seen that the magnitude of this term is related to the relativechanges in work function on the wafer surface 16 and relative speed atwhich the nvCPD sensor 12 is moved over the wafer surface 16. Anillustration of the signal generated from this can be seen in FIG. 4.Thus, a system in accordance with the principles of the presentinvention is capable of generating one-dimensional signals andtwo-dimensional images, although three-dimensional images can begenerated.

Many defects can present themselves as variations in the wafer workfunction or the overall surface potential. Both chemical and physical(i.e., geographical) features of the wafer surface and the underlyingmaterials can affect the work function of a particular portion or even asingle point on the wafer surface; thus, these features can be detectedby a sensor in accordance with the principles of the present invention.For instance, variation in semiconductor dopant concentrations in thewafer 15 will cause varying characteristic work functions. In addition,other materials that could diffuse into the wafer 15, such as but notlimited to copper, will cause variations in work function. Within thesemiconductor material (or any other material susceptible tomeasurement) itself, mechanical phenomena such as dislocation pile-ups,cracks, and scratches generate local stresses which will change thelocal work function. In addition, adsorbed layers of atomic or molecularcontaminants even at the sub monolayer level will generate appreciablesurface potential variations. Particles deposited on the wafer 16 with asurface potential different than the surrounding wafer material willalso create a signal. Layers of chemicals commonly used in the waferfabrication process will affect the surface potential of the wafer. Forinstance residual CMP slurry or photo-resist would cause localvariations in surface potential detectable by the nvCPD sensor 12 of thepresent invention. Such defects and chemistry have associated with themcharacteristic signatures which enable inspection of the wafer surface.

The

$V\frac{\partial C}{\partial t}$term is related to changes in gap between the nvCPD sensor 12 and thewafer 15 or variations in the relative dielectric constant. Geometricalimperfections in the wafer surface 16 or particles on the wafer surface16 would manifest themselves in this component. Also because of itsdifferential nature, the magnitude of this component would also increaseas the relative speed of the nvCPD sensor 12 to the wafer 15 isincreased.

As previously mentioned, physical or geographical aspects and defectscan be imaged using a system in accordance with the principles of thepresent invention. Many classes of wafer defects would appear asgeometrical changes in the wafer surface 16. In the wafer 15 itself,surface cracks, scratches, etched trenches, etc. would be nonlimitingexamples of such defects causing a geometrical change in the wafersurface and an attendant change in the work function. In addition,particles deposited on the wafer 15 would also present themselves as alocal change in the distance to the probe sensor tip 13.

Variations of dielectric films on the wafer 15 can also be detected. Anexample would be detecting variations in the oxide state grown on thesilicon substrate (i.e. SiO, SiO₂, SiO₃, SiO₄). In addition, variationsin dielectric of other non-conducting materials commonly deposited onthe wafer could be detected.

It should also be noted that many features could present themselves ascombinations of geometrical changes and chemical changes. For instance,a particle deposited on the wafer 15 of differing material than theunderlying wafer 15 could cause variation. Also, a crack in the surfacewould also induce stresses that would cause variations in local workfunction.

In FIG. 5 is schematically shown one form of the system 10 forapplication of the nvCPD sensor 12 to scan the wafer 15 for defects andcontamination. FIGS. 8A and 8B also illustrate more detailed drawings oftwo alternative operating embodiments of the system 10. The system 10 inFIG. 5 includes an X-Y-Z positioning system 26, a rotating wafer stage28, a high speed data acquisition system 30 with a personal computer(PC) 32, and control software executed by the PC 32.

As shown in more detail in FIG. 8A, in one embodiment, the wafer 15 isaffixed to a rotating spindle or chuck 54 (see FIG. 1) using a clampingfixture 56 on the wafer edges. A sensor positioning system 50 includesan nvCPD sensor 52 positioned a fixed distance from the wafer 15 ismounted to a spindle 54. The wafer 15 (not seen in this view) is thenrotated at high speed, and the nvCPD sensor 52 is translated radially tocollect data in circumferential tracks. The scanning procedure as shownschematically in FIG. 9 lasts between a few seconds and several minutes,depending on the number of scanned tracks, the speed of the spindle 54,and the speed of the sensor positioning system 52. The tracks of dataare then put together to form a CPD image. These CPD images allow thevisualization of chemical and geometrical defects and thereby enableclassification of the type of defect present on the wafer surface. Someexamples of these CPD images can be seen in FIG. 10A-15 and are takenfrom a 100 mm wafer compared with optical images of the same wafer (see,Example infra). The present invention is capable of generating imagemaps of one atomic layer thick patterns, as shown in FIG. 21A. FIG. 21Billustrates the signal strength as the wafer is rotated relative to theprobe, thus passing over defects and features of the wafer surface. Asshown in FIG. 21C, the present invention, in fact, detected sputteredgold at densities less than a single atomic layer.

The images generated by the scanning procedure of FIG. 9 weresubsequently processed to automatically locate defects; thus locatingareas of high variability. An ideal surface would exhibit a flat signal,but a wafer surface with defects would exhibit some variability in thesignal. To locate areas with defects, the data was broken up in to smallareas of known location. The standard deviation of the signal withinthese areas was determined. Areas with defects showed a higher standarddeviation, and these results can be seen in FIG. 6. Areas with defectsappear brighter than lower variability areas of the wafer 15. This isone of many possible methods in accordance with the principles of thepresent invention to process the sensor data.

More generally, a defect can be identified by one or more of thefollowing:

-   -   Process the data to look for a voltage or change in voltage (or        pattern of voltages or changes in voltages) that exceeds some        user-defined value (threshold).    -   Compare the data to a known pattern that represents a defect via        some form of correlation or template matching.    -   Convert the spatial data to the frequency domain and then        identify peaks in the frequency domain that represent defects        with unique spatial characteristics.

These techniques can also be combined with other techniques to yieldanalytical results. The signal may also be preprocessed to facilitatedefect detection, such as, for example:

-   -   Since the signal is differential, it can be integrated over some        distance to produce voltages that represent relative CPD's over        the surface of the wafer 15.    -   If the wafer 15 is “patterned”, then this known pattern can be        removed from the data prior to processing. This would likely be        accomplished through some conventional method of variation of        image or signal subtraction in either the space or frequency        domains.    -   The signal would likely be processed with some form of frequency        filtering to remove high or low frequencies depending on the        size, shape and other characteristics of the expected defects.    -   The signal could be processed to remove features of a certain        size by doing what is called “morphological processing” which is        well known in the art.

In one embodiment, a defect is detected and the contamination level isquantified based on an edge detection algorithm, such as but not limitedto Canny Edge detection algorithm. Multiple resolutions may be used ormultiple scales or a combination thereof. FIGS. 22B-F depict the edgedetection at various resolutions and in comparison to an optical image(FIG. 22A). FIGS. 23B-F depict edge detection at various scales and incomparison to an optical image (FIG. 23A). In a preferred example ofsuch an embodiment, the contamination is detected and quantified usingthe steps of:

-   -   Generating a CPD sensor peak signal at the boundary between two        different areas (The peak signals behave much like the “edges”,        an image processing term. So, the contaminated area can be        located by edge detection.);    -   Apply an Edge detection algorithm (such as the 2D Canny        algorithm);    -   Multiple resolutions with different thresholds (thereby enabling        detection of various size of contaminants, i.e. the higher        resolution (lower threshold) will find the smaller        contaminants);    -   Quantifying contamination level (CL) by the edge area over the        total wafer area in the simplest way.

As previously discussed, determining a reference point for the sensor isnecessary for optimal results. In one embodiment, the reference point isat the center of rotation (in the X-Y plane) and at the height of thesurface of the wafer (on the Z axis). To find this point, the center ofrotation and the height of the surface of the wafer must be determined,and then the height sensor is correlated with the Z position of thenvCPD sensor.

To find the center of rotation, the nvCPD sensor and motion system areused to find a geometrical or chemical feature on the surface of thespinning wafer at three or more points. Since the wafer is spinning, thefeature describes a circle. The center of the circle is the center ofrotation. Given the coordinates of three distinct points (A(x₁,y₁),B(x₂,y₂), and C (x,y)) on the diameter of the defined circle on thecircle, its center is found algebraically by the equation:(x−x ₁)(x−x ₂)+(y−y ₁)(y−y ₂)=0.Due to slight measurement errors, a different set of points might yieldslightly different center coordinates. The “true” center of rotation isdeemed to be the locus (average) of these points.

In one embodiment, to find the height of the surface of the waferwithout touching the wafer surface, two sensors, the nvCPD sensor and aheight sensor (which could itself be an nvCPD sensor in an embodimentdiscussed below) can be used. The nvCPD sensor and height sensor arecalibrated so that when a reading is taken with the height sensor, theZ-axis coordinate of the tip of the nvCPD sensor is ascertained. (Thiscalibration procedure is described below.) At that point, the readingsof the height sensor are correlated with the Z position of the nvCPDsensor. Thereafter, the height sensor is used to detect the position ofthe surface of the wafer without touching it and then the tip of thenvCPD sensor positioned accordingly.

In one embodiment, the height sensor is correlated with the Z positionof the nvCPD sensor based on two assumptions: first, that within itsusable range, measurements from the height sensor are linear in the Zaxis and that a constant, k, can map changes in height measurements toproportional changes in Z; and second, that the relative positions ofthe height sensor and nvCPD sensor are fixed, i.e. the two sensors canmove relative to the rest of the world but only as a unit; they,therefore, cannot move independently. Based on these assumptions, apoint, P, is picked in the X-Y plane where calibration is to beperformed. The height sensor is positioned above P, and a measurementfrom the height sensor, Hm, correlated with a coordinate on the Z axis,Zh. Next the nvCPD sensor is positioned above P and move it down untilit touches at a point, Zc. The nvCPD signal changes significantly whenthe sensor tip touches the surface. Once these values are known, the Zvalue of the point where the tip of the nvCPD sensor would touch thesurface is derived with the following equation:Z _(surface) =Z _(current) +Z _(c) −Z _(h)+(H _(m) −H _(current))/kwherein:

-   Z_(surface) is the height of the surface where the tip of the nvCPD    sensor would touch-   Z_(current) is the current height of the sensor-   H_(current) is the current height sensor measurement

As previously mentioned, the height of the sensor should be measured andcontrolled to produce repeatable results. It is also possible to use annvCPD sensor to control the height in a semiconductor wafer inspectionsystem in accordance with the principles of the present invention. Inorder to use the nvCPD sensor to control height, the system must providethe capability to apply a time-varying bias voltage between the probetip and the wafer surface. As the bias voltage varies, it produces anoutput signal that is a function of the capacitance between the probetip and the wafer surface. The closer the probe tip is to the surface,the larger the output voltage. After the relationship between height andcapacitance is determined, the magnitude of the output signal can beused to calculate the height of the sensor. The signal magnitude can becalculated as the peak-to-peak, standard deviation, RMS, or some othermeasure known in the art.

Again, the formula for the output of the nvCPD sensor is:

$i = {{C\frac{\partial V}{\partial t}} + {V\frac{\partial C}{\partial t}}}$The voltage V is the contact potential difference between the probe tipand the wafer surface. If a bias voltage is applied, the formula thenbecomes:

$i = {{C\frac{\partial( {V + {Vb}} )}{\partial t}} + {( {V + {Vb}} )\frac{\partial C}{\partial t}}}$where Vb is the bias voltage. If the nvCPD sensor is not moving relativeto the surface of the wafer (or is moving relatively slowly), then thecapacitance C and the contact potential difference voltage V are notchanging, and the equation becomes:

$i = {C\frac{\partial{Vb}}{\partial t}}$

Since the bias voltage is a known fixed frequency and magnitude, theoutput current is a function of the capacitance (C). C is a combinationof the capacitance between the probe tip and wafer surface, and anystray capacitances in the circuit. The capacitance vs. height functioncan be characterized and used to determine the height of the nvCPD probeat a point above the wafer surface. Once the height of the sensor isdetermined, then the bias voltage can be turned off in order to makescanning nvCPD measurements.

However, in some embodiments prior to scanning a portion of the wafer, aheight profile is established with a height sensor and then the scanningheight of the nvCPD sensor adjusted appropriately. FIG. 18 depicts oneembodiment which utilizes a height profile of the wafer to position thesensor. The height profile is determined by first moving the heightsensor to the center of rotation and then, with the wafer spinning, theheight sensor is moved out toward the edge of the wafer until it sensesthe edge. Note that this also allows the diameter of the wafer to bedetermined. The sensor is then moved back toward the center until it iswithin the wafer flat(s) or notch. One or more height measurements takenalong the way establish the profile. An appropriate height for nvCPDsensor scanning is calculated based on the profile, particularly basedon the maximum detected height.

As mentioned above, often nvCPD sensors used in accordance with theprinciples of the present invention generate a peak signal that behaveslike noise. In accordance with the principles of the present invention,denoising algorithms can be applied to both nvCPD signals and nvCPDimages. In one embodiment, the nvCPD signal/image data are decomposedinto the wavelet domain using one of the wavelets available such as butnot limited to ‘Coiflet’, ‘Daubechies’, ‘Symmlet’, and other suchwavelets. Then, as a result of the wavelet decomposition, a series ofwavelet coefficients are obtained at a finite number of scales that canbe given by the user. A coefficient at a particular scale represents themagnitude of the frequency corresponding to that scale at the pointcorresponding to that coefficient. The nvCPD signal/image can then bereconstructed by the coefficients in reverse order.

By adjusting the coefficients and performing reconstruction, the threecomponents (peak, low frequency, and noise) of the nvCPD signal/imagecan be selectively filtered out. To eject the low frequency componentfrom the nvCPD signal/image, only wavelet coefficients at fine scalesare used for reconstruction since the low frequency component of thenvCPD signal/image are represented by the coefficients at coarse scales.To eject the noise from the nvCPD signal/image, the coefficients at finescales can be shrunk softly based on the threshold given. The thresholdcan be determined using any one of numerous methods known in the artsuch as, but not limited to, ‘Visu’, ‘SURE’, ‘Hybrid’, ‘MinMax’. Thesharp peak signal that is related to contamination on the wafer can bereconstructed substantially in isolation by the wavelet coefficientsresulting after the two processes above. Thus, noise such as vibrationsor a wobbling of the wafer can be filtered out of the signal. FIG. 19depicts an image produced by a system in accordance with the principlesof the present invention without deconvoluting or denoising the data.FIG. 20 illustrates the improved resolution and definition of an imagewhich is denoised in accordance with the principles of the preferredembodiment.

A semiconductor wafer inspection system in accordance with theprinciples of the present invention which utilizes a nvCPD sensor may,as discussed above, experience a time delay. However, the presentinvention provides a filtering technique to remove this time delay.First, the time delay circuit is modeled as a first order RC circuit.The continuous-time transfer function of the RC circuit is given by

$\frac{Y(s)}{X(s)} = \frac{1}{{\tau\; s} + 1}$where X(s) and Y(s) are the Laplace transformation of the input currentsignal at the probe tip and the output voltage measurement to the dataacquisition, and T is the time delay constant.

The continuous current signal is fed into and amplified by theamplifier, and then converted into a discrete signal through the A/Dconverter. In this way, the collected data by the computer at the finalstage is a series of discrete data. For digital signal processing, thecontinuous-time transfer function of the RC circuit is converted into adiscrete-time transfer function based on Z-transformation. Thisdiscretized transfer function has the form

$\frac{Y(z)}{X(z)} = \frac{\alpha}{z + \beta}$wherein the constants α and β are determined by the discretizationmethod employed, the sampling time and the time delay constant, τ.

Next, in a preferred embodiment, the impulse response of the discretizedtransfer function is determined. In general, the impulse response is afinite number of positive discrete values that converges to zerogradually. Once the impulse response is found, the deconvolution processwith the impulse response is performed on each track data separately.

Time constant prediction is important and can be assessed by comparingthe positive peak height and the negative peak height. FIG. 16 shows atypical nvCPD signal where there is a pair of a positive peak and anegative peak. It is shown that the positive peak is higher than thenegative peak. With zero time delay, the signal would look like FIG. 17,where the positive peak height is equivalent to the negative peakheight.

By comparing the positive peak height with negative peak height, thetime constant can be estimated correctly. If the time constant isunderestimated, the former peak (in this example, the positive peak) ishigher than the latter peak (in this example, the negative peak). If thetime constant is overestimated, the former peak is lower than the latterpeak. By varying the time constant, a point when the positive andnegative peaks are equivalent in height could be found to predict thetime constant correctly.

The following non-limiting example describes methods of preparation oftest wafers and sensing characteristic images for identifying certaindefect states, chemical states, electrostatic states and mechanicalfeatures present on a semiconductor wafer surface.

EXAMPLE

Sample wafers can be created by dip coating the wafer 15 in solutionsthat contain known concentrations of contaminants. Part of this exampledescribes metal contaminants such as Cu and Fe, although any manner ofchemical contaminants can be evaluated in this way. The wafer 15described is either a 100 mm or 150 mm wafer, although these examplesapply to any size wafer. The wafer surface 16 is prepared by dipping inHF to remove oxides. The wafer 15 is then cleaned and partially dippedin the metal contaminant solution. The amount of solution remaining onthe wafer 15, and the resulting concentration of contaminant on thewafer surface 16, is controlled by selecting dip coating parameters suchas the extraction rate.

Partial dipping of the test wafer 15 is preferred to create a transitionfrom clean to contaminated areas. Because the nvCPD signal isdifferential, the nvCPD sensor 12 detects changes on the wafer surface16, as opposed to an absolute value relating to surface condition. Thisaspect of nvCPD sensors 12 is offset by the ability to rapidly image anddetect localized contamination anywhere on the surface of the wafer 15.

After preparation, each test wafer 15 can be, if necessary, analyzedusing an appropriate combination of XPS, Auger, and RBS (or other wellknown surface analysis methods) techniques to measure actual contaminantconcentrations in the dipped areas of the wafer 15. Each step involvedin the sample wafer preparation process is shown in FIG. 7. In aproduction line methodology, standards can be established correlatingmeasure actual contamination concentration to nvCPD data for routineuse.

After each sample wafer 15 is created, it can be imaged using a radiallyscanning nvCPD imaging system 10 constructed in accordance with theinvention. As described before, FIGS. 8A and 8B show basic forms of thenvCPD imaging system 10, and FIG. 9 shows another flow diagramillustration of wafer processing. The system 10 employs the nvCPD sensor12 mounted on the previously described three-axis positioning system 26.This positioning system 26 is used to position the nvCPD sensor 12 abovethe wafer surface 16 to be imaged, and to scan the nvCPD sensor 12radially across the wafer surface. The wafer 15 is mounted on a spindlethat rotates at high speed (1800 rpm) beneath the nvCPD sensor 12. Thesystem 10 operates by acquiring multiple consecutive tracks of data asthe nvCPD sensor 12 is stepped along the radius of rotation of the wafer15.

The imaging system 10 has been used for a variety of surface analysisexperiments. FIGS. 10A, 10B, 11A, and 11B show sample wafer images thatwere generated using the nvCPD sensor 12 imaging for wafer inspection.The images show optical images in FIG. 10A and 11A and nvCPD images inFIG. 10B and 11B of a 100 mm form of the wafers 15. The first wafer 15was cleaned, and then a small vacuum pick-up device was attached to thesurface of the wafer 15 in three locations. The optical image of FIG.10A shows no evidence of any change on the surface 16 of the wafer 15.The nvCPD image of FIG. 10B shows a very large signal at the locationswhere the pick-up device was applied. The nvCPD signal is believed to bethe result of a small amount of residue left on the surface 16 by thepick-up device.

The second set of images in FIGS. 11A and 11B show a wafer 15 that hashad alcohol spun-on and then dried. The resulting residue is not visiblein the optical image FIG. 11A, but is clearly visible in the nvCPD imageFIG. 11B. These images provide a clear demonstration of the usefulnessof nvCPD sensor 12 for wafer inspection. Through careful measure of afull mage of defect states and chemical constituents it is possible tocorrelate an image with a particular chemical state, defect, orcombination thereof.

FIGS. 12A and 12B show, respectively, an optical image of latex glovemarks and a nvCPD image of latex glove marks. FIGS. 13A and 13B show,respectively, an optical image of human fingerprints and an nvCPD imageof the fingerprints. FIG. 14 shows a nvCPD image of a wafer 15 afterbrushing the wafer 15 with a stainless steel tool, and FIG. 15 shows anvCPD image of the wafer 15 after pressing an aluminum fixture onto thewafer surface 16. All these example images were acquired using the nvCPDsensor 12 with the probe sensor tip 14 having a diameter ofapproximately 60 microns measured over a period of approximately 30seconds.

While preferred embodiments of the invention have been shown anddescribed, it will be clear to those skilled in the art that variouschanges and modifications can be made without departing from theinvention in its broader aspects as set forth in the claims providedhereinafter.

1. A method of identifying a defect and performing a quality inspectioncomprising the steps of: providing a wafer having a surface; providing anon-vibrating contact potential difference sensor; scanning thesemiconductor wafer relative to the non-vibrating contact potentialdifference sensor, the scanning step generating a signal from changes incontact potential difference; generating contact potential differencedata from the signal from changes in contact potential difference;processing the non-vibrating contact potential difference sensor data toautomatically detect a pattern that represents the defect; andoutputting the pattern that represents the defect in order to carry outa quality inspection of the wafer.
 2. The method as defined in claim 1further comprising the step of determining a scanning height of thenon-vibrating contact potential difference sensor to provide an improvedquality inspection of the wafer.
 3. The method as defined in claim 2,wherein the step of determining the scanning height comprisespositioning a height sensor that is fixed relative to the non-vibratingcontact potential difference sensor; measuring a distance between theheight sensor and the wafer; and correlating the height sensormeasurements with the non-vibrating contact potential difference sensorposition.
 4. The method as defined in claim 3, wherein the step ofdetermining the scanning height further comprises providing atime-varying bias voltage, and further wherein the height sensor is thenon-vibrating contact potential difference sensor.
 5. The method asdefined in claim 1, further comprising the step of determining areference point for optimizing the quality inspection of the wafer. 6.The method as defined in claim 5, wherein the reference point is thecenter of the wafer as determined by: positioning the non-vibratingcontact potential difference sensor above the wafer; spinning the wafer;detecting at least three features on the surface of the wafer; andcalculating the center of the circle defined by the at least threefeatures.
 7. The method as defined in claim 6, further comprising thestep of determining a height profile of the wafer by the steps of:positioning the height sensor above the center of the spinning wafer;and moving the height sensor to the outer edge of the wafer.
 8. Themethod as defined in claim 7, further comprising the step of determiningthe diameter of the wafer.
 9. The method as defined in claim 1, furtherincluding the step of reducing noise in the contact potential differencedata which comprises deconvoluting the contact potential difference datafor improving the quality inspection of the wafer.
 10. The method asdefined in claim 1 further comprising the step of reducing the noise inthe non-vibrating contact potential difference data for improving thequality inspection of the wafer.
 11. The method as defined in claim 10,wherein the step of reducing the noise further comprises: decomposingthe non-vibrating contact potential difference data into a waveletdomain; producing a series of wavelet coefficients at a finite number ofscales; reconstructing the data using only fine scales; and shrinkingthe fine scales based on a given threshold.
 12. The method as defined inclaim 11, wherein the peak signal is selected by selecting only waveletcoefficients at fine scales and by shrinking the fine scale coefficientsbased on a threshold.
 13. The method as defined in claim 12 wherein thethreshold is determined by a wavelet thresholding method selected fromthe group consisting of “Visu”, “SURE”, “Hybrid”, and “MiniMax”.
 14. Themethod as defined in claim 1, further comprising the step of removing atime delay from the non-vibrating contact potential difference sensordata for improving the quality inspection of the wafer.
 15. The methodas defined in claim 1 further including the steps of: displaying thecontact potential difference data on a display to generate acharacteristic wafer image; and comparing the characteristic wafer imagewith stand images to identify the category of defect present on thesurface of the wafer.
 16. The method as defined in claim 1, wherein thestep of processing the sensor data includes assembling of the data fromthe contact potential difference sensor into an image that is displayedto the user for evaluation by the user.
 17. The method as defined inclaim 1, wherein the step of processing the sensor data includesautomatically processing the contact potential difference data toidentify the category of defect detected.
 18. The method as defined inclaim 1, wherein the scanning step includes moving the wafer.
 19. Themethod as defined in claim 18, wherein the step of moving the wafercomprises spinning the wafer.
 20. The method as defined in claim 1,wherein the wafer includes at least one additional layer disposed on abase silicon wafer.
 21. The method as defined in claim 1, wherein thedefect is taken from the group consisting of a mechanical defect, achemical defect, an electronic defect, and combinations thereof.
 22. Themethod as defined in claim 1, wherein the step of scanning comprises thesensor being displaced relative to a fixed form of the wafer.
 23. Themethod as defined in claim 1, wherein the step of scanning includesmoving both the wafer and the sensor.
 24. The method as defined in claim1, wherein the step of comparing comprises performing a patternrecognition methodology.
 25. The method as defined in claim 1 furthercomprising the step of processing the wafer with a treatment forameliorating the category of defect identified.
 26. The method asdefined in claim 1 further comprising the step of performing asupplementary analysis.
 27. The method as defined in claim 26, whereinthe step of performing a supplementary analysis comprises analyzingchemical contaminants.
 28. The method as defined in claim 27, whereinthe step of analyzing chemical contaminants comprises at least one ofx-ray photoelectron spectroscopy, Auger spectroscopy and Rutherfordbackscattering.
 29. The method as defined in claim 1 further includingthe step of applying a computerized decisional methodology to rejectselected ones of the semiconductor wafers having an unwanted category ofdefect.
 30. The method as defined in claim 1 further including the stepof detecting the defect using an edge detection application.
 31. Themethod as defined in claim 30, wherein detecting the defect using theedge detection application comprises the steps of: generating a CPDsensor peak signal at a boundary between two different areas; applyingan Edge detection application at more than one resolution with differentthresholds; and quantifying contamination level by the edge area overthe total wafer area.
 32. A method of denoising signal data from anon-vibrating contact potential difference sensor inspecting a wafer,comprising the steps of: generating signal data from a contact potentialdifference sensor characteristic of a surface of a wafer; decomposingthe signal data into a wavelet domain; obtaining a plurality ofcoefficients at a finite number of scales; selecting for a peak signalselected by selecting only wavelet coefficients at fine scales and byshrinking the fine scale coefficients based on a threshold;reconstructing the data by the coefficients in reverse order; andoutputting the reconstructed data to carry out an improved qualityinspection of the wafer.
 33. The method of claim 32, wherein thethreshold is determined by a wavelet thresholding method selected fromthe group consisting of “Visu”, “SURE”, “Hybrid”, and “MiniMax”.
 34. Themethod of claim 32, wherein the signal data is decomposed into thewavelet domain using a wavelet selected from the group consisting of“Coiflet”, “Daubechies”, and “Symmlet”.
 35. A method of removing a timedelay from a non-vibrating contact potential difference sensor signalfrom inspecting a wafer, comprising the steps of: generating anon-vibrating contact potential difference sensor signal characteristicof a wafer; modeling a circuit as a first order RC circuit; convertingthe non-vibrating contact potential difference sensor signal into adiscrete time transfer function; determining the impulse response of thediscretized time transfer function; deconvoluting each data trackseparately to produce a deconvoluted sensor signal; and outputting thedeconvoluted sensor signal to carry out a quality inspection of thewafer.
 36. A system for identifying a category of defect on a surface ofa wafer, comprising: a non-vibrating contact potential differencesensor; a height sensor for measuring height of the contact potentialdifference sensor above the surface of the wafer to control the heightand thereby produce repeatable identification of the category of defect;a device for moving the non-vibrating contact potential differencesensor relative to the semiconductor wafer; and a computer for receivingand analyzing wafer data generated by the non-vibrating contactpotential difference sensor and the height sensor and processing thenon-vibrating contact potential difference sensor and the height sensordata to automatically detect a pattern that represents a defects. 37.The system as defined in claim 36, wherein the height sensor is anon-vibrating contact potential difference sensor.
 38. The system asdefined in claim 36 further including a data base of images of standarddefects, and wherein the computer including computer software which cananalyze the wafer data and compare with the images of standard defectsto generate identification information about the type of defect presenton the surface of the wafer.
 39. The system as defined in claim 36further including a transport device to move selected ones of thesemiconductor wafers to a secondary processing system having a categoryof defect which can be remedied.
 40. The system as defined in claim 39,wherein the transport device comprises a wafer handler.
 41. The systemas defined in claim 36 further including a plurality of the sensors withone of the sensors disposed immediately downstream from each of aplurality of cleaning systems, thereby enabling monitoring of thesemiconductor wafer after processed at each of the cleaning systems. 42.The system as defined in claim 36, further including a mechanism forautomatically determining the cleanliness of wafers and modifyingcleaning parameters to improve the cleaning process.
 43. The system asdefined in claim 36, wherein the wafer is a semiconductor wafer.
 44. Amethod of identifying a defect comprising the steps of: providing awafer having a surface; providing a reference source for dataprocessing; providing a non-vibrating contact potential differencesensor; scanning the semiconductor wafer relative to the non-vibratingcontact potential difference sensor; generating contact potentialdifference data from the non-vibrating contact potential differencesensor; processing the non-vibrating contact potential difference sensordata to automatically detect a pattern that represents the defect withthe reference source enabling at least one of signal generation, imageproduction and absolute distance measurement; and utilizing the patternthat represents the defect to carry out a quality inspection of thewafer.